Katsuhide Warashina

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This paper studies the characteristics of a new composite evolutionary computation algorithm in which genetic evolution, individual learning and social learning interact in NK fitness landscape. We derive conditions for effective social learning in static and dynamic environments using computer simulations of a model of the composite evolutionary algorithm.(More)
This paper studies the characteristics of interaction among genetic evolution, individual learning and social learning using an evolutionary computation system with NK fitness landscape, both under static and dynamic environments. We show conditions for effective social learning: at least 1.5 times lighter cost of social learning than that of individual(More)
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